Chapter 143 23.3 Surprising Trivia

The final chapter of this book is a short course in the nature of complex adaptive systems and control that we, or at least I, do not understand.It's a list of problems, a catalog of gaps.Even to non-scientists, many of these questions may seem silly, trivial, trivial, or barely worth mentioning.Similarly, experts in related fields may say that these problems are the disturbing madness of science enthusiasts, and the meditation of technology transcendentalists behind closed doors, and it doesn't matter.And I read a wonderful passage that inspired me to write this unconventional course.That wonderful passage was written by Douglas Hofstadter, predating Penti Canelva's obscure monograph on sparsely distributed computer memory techniques.Hofstadter wrote:

Being surprised by a problem that no one is interested in, or by a problem that no one thinks is a problem, is perhaps a better example of scientific progress. My astonishment at how nature and machines work is the fundamental motivation for writing this book.I wrote this book as an effort to explain my confusion to the reader.When I write about something that I don't understand, I will compete with it, study it carefully, or read a lot of related books until I understand it, and then start writing again until I am stumped by the next question.Afterwards, I would repeat the process, over and over again.I always run into problems that stop writing from going on.Either no one answered the question, or someone simply didn't understand my confusion and gave a clichéd answer.These roadblocking issues never seemed so overwhelming in the first place, and became a problem that prevented me from continuing.But in fact they are prototypical heterogeneous.Just as Hofstadter was amazed and appreciated by the human mind's ability to classify objects before they are recognized, so too will these unsolved mysteries yield profound insights in the future, perhaps revolutionary understandings, and perhaps ultimately Become the accepted thing we have to explain.

Readers may be puzzled to see that most of the questions listed here seem to be questions that I have already answered in the preceding chapters.In fact, all I do is circle around these problems, measure their range, and climb up until I get stuck at some false apex.In my experience, obsessing over some of the answers elsewhere tends to lead to most of the good questions.This book is an attempt to find interesting problems.But on the way to explore, some really common problems stuck with me.Here are the questions. I use the word "emergence" a lot in this book.Among the complicating-everything professionals, the term has something of the meaning: "an organization of parts acting in unison."But when we read the word without vague impressions, its emerging meaning gradually disappears, and the word has no special meaning in fact.I've tried replacing "emerge" with "happen" everywhere I use "emerge" and it seems to work just fine.We can try.Global order emerges from local rules.What do we mean by emerging?

Then there's "complexity," what exactly is it?I pinned my hopes on two scientific books published in 1992, both titled Complexity, by Mitch Waldrop and Roger Lewin, because I hoped that one of them would provide practical measure of sex.But both authors have written books on the subject without risking a useful definition.How do we know that one thing or one process is more complex than another?Are Cucumbers More Complicated Than Cadillacs?Are grasslands more complex than mammalian brains?Are zebras more complex than national economies?I know that there are three or four mathematical definitions of complexity, but none of them can roughly answer the kind of questions I just posed.We are so ignorant of the complexity of things that we have not been able to ask the right questions about what complexity is.

If evolution is getting more complex, why?If this is not the case, why does it appear to be?Is complex really more efficient than simple? There seems to be a "required variety"—a minimum of complexity or variation among individuals—for processes such as self-organization, evolution, learning, and life and death.How can we know for sure when enough diversity is enough?We don't even have a proper measure of diversity yet.We have an intuitive feeling, but we can't translate it into anything very precisely.What is diversity? "Edge of Chaos" often sounds like "the mean of everything".Is this simply a Goldilocks-and-the-Bears trick to define the maximum adaptiveness of a system as "just adaptation"?Is this another necessary verbiage?

There is a famous Church/Turing conjecture in computer science theory, which strengthens most of the reasoning of artificial intelligence and artificial life research.The hypothesis is this: Given infinite time and infinite computing tapes, a general-purpose computing machine can compute anything that another general-purpose computing machine can compute.But my God!Infinite time and space are precisely the difference between life and death.Death has infinite time and space.To be alive exists in limitation.To a certain extent, then, there is a real limit to the substitutability of processes when the computational process is independent of the hardware on which it runs (one machine can emulate everything another machine can do).The prerequisite for the establishment of artificial life is to be able to extract life from its carbon-based carrier and make it start to operate in other different mother bodies.Experiments so far show that this is more true than expected.So where is the boundary between real time and real space?

What exactly is inimitable? All quests for artificial intelligence and artificial life are focused (some say trapped) on one big puzzle, namely, is a simulation of an extremely complex system a falsification, or is it something real in its own right?Maybe it's surreal, or maybe the term surreal begs the question.No one doubts the ability of the model to imitate the original.The question is: what kind of reality do we grant an object to simulate?What exactly is the difference between a simulation and an ontology? How far can you condense a meadow, so that it is reduced to a seed?That's the question that prairie restorers are inadvertently asking.Can you reduce the precious information contained in the entire ecosystem to a few bushels of seeds?When watered, will these seeds reproduce the awesome complexity of prairie life?Are there any important natural systems that simply cannot be reduced to size and accurately simulated?Such a system should be itself in its smallest compressed form, its own model.Are there man-made grand systems that cannot be condensed or distilled?

I would like to know more about stability.If we build a "stable" system, is there any way to define this stability?What are the constraints, necessary conditions for stable complexity?When is change no longer change? Why do species go extinct?If everything in nature adapts to the environment effectively at any time, spares no effort to overcome its opponents in the competition for survival and utilizes its environmental resources, why do some species still become obsolete?Maybe some organisms are better adapted than others.But why does the general mechanism of nature sometimes work for all living things and sometimes not benefit all living things, allowing some particular populations to decline and others to grow?To put it more bluntly, why do some organisms exhibit good dynamic adaptations and others do not?Why would nature acquiesce in some biological types being forced into naturally inefficient forms?Here's an example of an oyster-like bivalve that evolved an increasingly spiral-shaped shell that was barely open until the species went extinct.Why can't this organism evolve back into the applicable range?Why did the extinction happen in the same group, as if it were the fault of bad genes?How did nature produce an entire population of bad genes?Perhaps, the extinctions were caused by foreign objects, such as comets and asteroids.Paleontologist Dave Knopp hypothesizes that 75 percent of all extinction events are caused by asteroid impacts.If there were no asteroids, wouldn't there be extinctions?If all species on the earth had not become extinct, what would people be like today?For that matter, why do complex systems of any kind fail or die?

On the other hand, in this world of co-evolution, why is anything ultimately stable? I've heard every data on natural and man-made self-sustaining systems show that the system's self-stabilizing variation rate is between 1% and 1/10,000.Is such a rate of variation common? What are the downsides of connecting everything? Of all the possible spaces in which life exists, life conceived on Earth represents just one tiny sliver—a creative endeavor.Is there a limit to the amount of life that a given mass of matter can hold?Why aren't there more different kinds of life forms on Earth?How can the universe be so small?

Will the laws of the universe evolve?If the law governing the operation of the universe is generated by the universe itself, will it be affected by the self-regulating force of the universe?Perhaps the special fundamental law that underpins all rational laws is in constant flux.Are we playing a game where all the rules are constantly being rewritten? Can evolution evolve its own purpose?If an organism that is just a dumb-associated agent can create a goal that evolves itself, can an organism that is also blind and dumb and at one point very dull, evolve a goal? So what about God?Artificial life researchers, evolutionary theorists, cosmologists, and simulation scholars cannot see the credit of God in their academic papers.But I am surprised that in some private occasions, these same researchers often talk about God.The God used by scientists is a technical concept, calm and composed, has nothing to do with religion, and is closer to the divine—the local creator.Whenever discussing the celestial world, including reality and models, God seems to be a precise algebraic symbol, replacing the ubiquitous X, operating outside a certain world, and creating that world. "Well, you're God..." a computer scientist muttered as he demonstrated a new program, meaning he was making the rules for the world.God is a shorthand for the eternal observer who makes things real.God then becomes a scientific term, a scientific concept.It has neither the philosophical subtleties of initial origin nor the theological finery of a creator; it is simply a convenient way of exploring the initial conditions necessary to run a world.So what do we ask of gods, what makes a good god?